Database management systems have long existed, but traditionally they have operated on bounded data. Bounded data comes in fixed sets. The words in a book and the names of all people who attended high school in 1992, for example, represent fixed sets of bounded data.
In contrast to bounded data, stream data is unbounded and is created in systems in continuous flows. Trade orders in a stock trading system and “call detail records” in a telecommunications system are both examples of data streams that are generally large in scale. The field of business intelligence (BI) has developed to “mine” large-scale continuous data in business settings and create applications to aid in decision-making processes.
In BI and in the more general field of data analytics, there is great interest in creating systems to efficiently handle the processing of data streams.
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